Soil Moisture Monitoring By Remote Sensing And Numerical Simulation Analysis

Soil moisture is an important influence factor of the land surface energy balanceand water cycle. It is the main parameters of the climate environment, water resources,ecological conditions, agricultural production and other fields. The Soil moistureplays an important part during the exchange and cycle of water and energy betweenthe land the surface and atmosphere interface.On the base of recent studies of home and aboard, utilizing the HeilongjiangProvince as the main study area, this paper uses the MODIS image data (Land SurfaceTemperature, Land Surface Albedo, Vegetation Index) of the year2005as the basicparameters for inverting the soil moisture, and sets the model ofrarity-vegetation-covered period (April, Month, September, October, November) bythe exponential model fitted by ATI with the actual soil moisture data provided by theNational Meteorological Center, then sets the model of dense-vegetation-coveredperiod (June, July, August) with the linear model fitted by the Vegetation TemperatureMixed State Index, remote sensing monitoring on regional soil moisture realized.NCEP data is used to generally evaluate the rationality and distribution trend of thesoil moisture distribution map.In order to research the changes of the soil moisture at different depths, on thebase of the Sanjiang Ecological Wetland data, this paper uses the CoLM model to dothe simulation test including soil moisture and temperature on the data. The testaccurately simulates the change trends of the soil moisture and temperature atdifferent depths. The simulation results are consistent with the actual measured data.At last, analysis the actually measured precipitation rate and the soil moisture timeseries to result the relationship between the change trends of the actual soil moistureand the precipitation, the simulation’s accuracy being validating.This paper includes six sections. The first section is the general introduction. Thesecond is the theories and methods of the soil moisture. The third introduces the studying area and the data source. The forth is the modeling of the soil moisture bythe remote sensing method. The fifth is the numerical simulation test and the sixthsection is the conclusion and the further expectation.